scholarly journals The Influence of Industrial Structure Upgrading on Carbon Emission Efficiency in China

2019 ◽  
Vol 10 (2) ◽  
pp. 7-15
Author(s):  
Luyan Song ◽  
Keyword(s):  
Carbon Emission ◽  
Industrial Structure ◽  
Emission Efficiency ◽  
Industrial Structure Upgrading

scholarly journals Analysis of Regional Differences and Influencing Factors on China’s Carbon Emission Efficiency in 2005–2015

Energies ◽  
2019 ◽  
Vol 12 (16) ◽  
pp. 3081 ◽  
Author(s):  
Zeng ◽  
Lu ◽  
Liu ◽  
Zhou ◽  
Hu
Keyword(s):  
Influencing Factors ◽  
Regional Differences ◽  
Carbon Emission ◽  
Industrial Structure ◽  
Tobit Model ◽  
Policy Implications ◽  
Dea Model ◽  
Emission Efficiency ◽  
Unit Root Testing ◽  
Technology Level

With the challenge to reach targets of carbon emission reduction at the regional level, it is necessary to analyze the regional differences and influencing factors on China’s carbon emission efficiency. Based on statistics from 2005 to 2015, carbon emission efficiency and the differences in 30 provinces of China were rated by the Modified Undesirable Epsilon-based measure (EBM) Data Envelopment Analysis (DEA) Model. Additionally, we further analyzed the influencing factors of carbon emission efficiency’s differences in the Tobit model. We found that the overall carbon emission efficiency was relatively low in China. The level of carbon emission efficiency is the highest in the East region, followed by the Central and West regions. As for the influencing factors, industrial structure, external development, and science and technology level had a significant positive relationship with carbon emission efficiency, whereas government intervention and energy intensity demonstrated a negative correlation with carbon emission efficiency. The contributions of this paper include two aspects. First, we used the Modified Undesirable EBM DEA Model, which is more accurate than traditional methods. Secondly, based on the data’s unit root testing and cointegration, the paper verified the influencing factors of carbon emission efficiency by the Tobit model, which avoids the spurious regression. Based on the results, we also provide several policy implications for policymakers to improve carbon emission efficiency in different regions.

scholarly journals Analysis and Evaluation of the Regional Characteristics of Carbon Emission Efficiency for China

2020 ◽  
Vol 12 (8) ◽  
pp. 3138 ◽  
Author(s):  
Jinkai Li ◽  
Jingjing Ma ◽  
Wei Wei
Keyword(s):  
Carbon Dioxide Emissions ◽  
Carbon Emission ◽  
Government Regulation ◽  
Industrial Structure ◽  
Western China ◽  
Energy Structure ◽  
Analysis And Evaluation ◽  
Emission Efficiency ◽  
Technological Efficiency ◽  
The Impact

To promote economic and social development with reduced carbon dioxide emissions, the key lies in determining how to improve carbon emission efficiency (CEE). We first measured the CEE of each province by using the input-oriented three-stage Data Envelopment Analysis (DEA) and DEA-Malmquist model for the panel data of 30 provinces in China during 2000–2017. Then we explored the CEE differences and characteristics of different regions obtained by using hierarchical clustering of each province’s CEE. Finally, based on the regression model, we conducted an empirical analysis of the impact of each factor of total factor productivity (TFP) on CEE. The main findings of this research are as follows: (1) The industrial structure, energy structure, government regulation, technological innovation, and openness had a significant impact on CEE; (2) The variation trends of CEE and TFP in the eight regions we studied were convergent, while the variations of CEE among regions were diverse and all distributed stably in different ranges; (3) The eight regions’ efficiency basically showed a downward trend of eastern, central and western China; (4) Technological regression was the main reason for the decline in TFP. Technological progress and technological efficiency can contribute to an improvement in CEE. Based on the findings above, we provide decision-making references for comprehensively improving the efficiency of various regions and accelerating China’s energy conservation, emissions reduction, and coordinated development.

scholarly journals Research on the spatial effect and threshold effect of industrial structure upgrading on carbon emissions in China

2021 ◽  
Author(s):  
Zhenqiang Li ◽  
Qiuyang Zhou
Keyword(s):  
Energy Consumption ◽  
Population Size ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Industrial Structure ◽  
Threshold Effect ◽  
Local Areas ◽  
The Impact ◽  
Consumption Intensity ◽  
Industrial Structure Upgrading

Abstract Based on panel data from 2000 to 2017 in 29 Chinese provinces, this paper analyzes the impact of industrial structure upgrading on carbon emissions by constructing a spatial panel model and a panel threshold model. The results show that (1) there is a significant spatial correlation between carbon emissions in Chinese provinces, and the carbon emissions of a province are affected by the carbon emissions of surrounding provinces; (2) in China, carbon emissions have a significant time lag feature, and current carbon emissions are largely affected by previous carbon emissions; (3) industrial structure upgrading can effectively promote carbon emission reductions in local areas, and the impact of industrial structure upgrading on carbon emissions has a significant threshold effect. With continued economic development, the promotion effect of industrial structure upgrading on carbon emission reductions will decrease slightly, but this carbon emission reduction effect is still significant. (4) In addition, there is a clear difference between the impact of energy consumption intensity and population size on carbon emissions in short and long terms. In the short term, the increase in energy consumption intensity and the expansion of population size not only increase the carbon emissions of a local area but also increase the carbon emissions of neighboring areas. In the long term, the impact of energy consumption intensity and population size on carbon emissions of neighboring areas will be weakened, but the promotion impact on carbon emissions in local areas will be strengthened.

scholarly journals Research on the Effect of Urbanization on China’s Carbon Emission Efficiency

2019 ◽  
Vol 12 (1) ◽  
pp. 163
Author(s):  
Lianshui Li ◽  
Yang Cai ◽  
Liang Liu
Keyword(s):  
Carbon Emission ◽  
Industrial Structure ◽  
Time Frame ◽  
Western Region ◽  
Eastern Region ◽  
Level Energy ◽  
Carbon Efficiency ◽  
Emission Efficiency ◽  
Expansion Form ◽  
The Western Region

Improvements in carbon emission efficiency are crucial to China’s economic growth; carbon emission reduction and urbanization are two of the focuses of research on carbon emission efficiency. This paper selects 2000–2015 panel data from 30 provinces in China, evaluates the carbon emission efficiency of each province using the DEA method and, based on the STIRPAT expansion form, empirically looks at the effect of urbanization on carbon emission efficiency. The results show that, during the chosen time frame, not only did the carbon emission efficiency of China’s provinces show an upward trend but the carbon emission efficiency of the Eastern, Central and Western regions differed markedly, with the highest efficiency in the Eastern region, the second highest in the Central region and the lowest in the Western region. After controlling for population density, economic development level, energy intensity and industrial structure, urbanization we determine that urbanization can indeed improve carbon emission efficiency, although there are regional differences. Urbanization is conducive to improvements in carbon emission efficiency in both the Central and Western regions but the promotion effect of the Western region is stronger. The effect in the Eastern region is not significant. Based on the conclusions above, this paper puts forward policy recommendations that promote both China’s lower carbon efficiency and future environmental protection.

scholarly journals Industrial Structure Transformation and Layout Optimization of Beijing-Tianjin-Hebei Region under Carbon Emission Constraints

2021 ◽  
Vol 13 (2) ◽  
pp. 643
Author(s):  
Yi Chai ◽  
Xueqin Lin ◽  
Dai Wang
Keyword(s):  
Carbon Emission ◽  
High Efficiency ◽  
Industrial Structure ◽  
Layout Optimization ◽  
Energy Structure ◽  
Structure Transformation ◽  
Low Carbon ◽  
Emission Efficiency ◽  
The Status ◽  
Low Efficiency

To address the issue of global warming, there is a trend towards low-carbon economies in world economic development. China’s rapid economic growth and high carbon energy structure contribute to its large carbon emissions. To achieve sustainable development, China must transform its industrial structure to conserve energy, reduce emissions, and adapt to climate change. This study measured the carbon entropy and carbon emission efficiency of 25 industries in the Beijing-Tianjin-Hebei region from 2000 to 2015 by building carbon entropy models and total factor industrial carbon emission efficiency evaluation models. The study showed that: (a) Priority development industries in the Beijing-Tianjin-Hebei region were expanding, the regional competitiveness of the moderate development industry was improving, and the proportion of restricted development industries had dropped significantly; (b) the spatial distribution of the three types of industries presented a pattern of concentric rings, with priority industries at the core, surrounded by moderate, then by restricted development industries; (c) the status of medium- and high-efficiency industries had improved, while the status of low-efficiency industries had decreased. Spatially, high- and low-efficiency industries were becoming concentrated, and medium-efficiency industries were becoming dispersed; (d) considering carbon entropy and carbon emission efficiency, the path of industrial structure transformation and upgrading and layout optimization in Beijing-Tianjin-Hebei region was proposed.

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